Gap formation and carbon cycling in the Brazilian Amazon: measurement using high-resolution optical remote sensing and studies in large forest plots

Espírito-Santo, Fernando Del Bon; Keller, Michael; Linder, Ernst; Oliveira, R. C. de; Pereira, Cleuton; Oliveira, Cleber Gonzales de

doi:10.1080/17550874.2013.795629

Cited by 28 publications

(21 citation statements)

References 57 publications

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“…2). A significant amount of CDW is associated with gap creation in intact Amazonian forests (Espírito-Santo et al, 2014a, b), and our models for logging confirm a strong relation between gap area and CDW. Considering both age since the last dis-turbance and number of degradation events in the historical models, gap area was still positively related to CDW stocks in logged forests, whereas the opposite trend was found in burned forests.…”

Section: Land Use Equationsupporting

confidence: 68%

“…For the historical models (2), we hypothesized that the CDW stock increases with the number of degradation events (Cochrane et al, 1999) and decreases with age since the last degradation event (Chambers et al, 2000). Additionally, we expected that the CDW stock increases with the increasing gap area (Espírito-Santo et al, 2014a) and with forest canopy height, a correlate of live aboveground biomass (Longo et al, 2016) because aboveground live biomass was significantly correlated with CDW across the Amazon (Chao et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

et al. 2019

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Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidarderived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.

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Section: Land Use Equationsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

et al. 2019

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“…However, deriving a mathematical relationship is challenging and factors other than tree size could influence gap sizes, including the spatial configuration of tree canopies within and among canopy strata, and the disturbance regime [72]. Multiple tree fall gaps are unusual in the humid equatorial tropics, where the death of single trees (or small groups of neighboring trees), is the predominant mechanism of canopy gap creation [73][74][75]. For example, analyses of the gap-sizes within ca.…”

Section: Gap Size Distributionsmentioning

confidence: 99%

Airborne LiDAR Detects Selectively Logged Tropical Forest Even in an Advanced Stage of Recovery

et al. 2015

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Identifying historical forest disturbances is difficult, especially in selectively logged areas. LiDAR is able to measure fine-scale variations in forest structure over multiple kilometers. We use LiDAR data from ca. 16 km 2 of forest in Sierra Leone, West Africa, to discriminate areas of old-growth from areas recovering from selective logging for 23 years. We examined canopy height variation and gap size distributions. We found that though recovering blocks of forest differed little in height from old-growth forest (up to 3 m), they had a greater area of canopy gaps (average 10.2% gap fraction in logged areas, compared to 5.6% in unlogged area); and greater numbers of gaps penetrating to the forest floor (162 gaps at 2 m height in logged blocks, and 101 in an unlogged block). Comparison of LiDAR measurements with field data demonstrated that LiDAR delivered accurate results. We found that gap size distributions deviated from power-laws reported previously, with substantially fewer large gaps than predicted by power-law functions. Our OPEN ACCESSRemote Sens. 2015, 7 8349 analyses demonstrate that LiDAR is a useful tool for distinguishing structural differences between old-growth and old-secondary forests. That makes LiDAR a powerful tool for REDD+ (Reduction of Emissions from Deforestation and Forest Degradation) programs implementation and conservation planning.

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“…These inventory techniques using thousands of plots, coupled with high-resolution remote sensing images, LIDAR, and GIS analysis were used to conduct carbon accounting procedures for producing maps of carbon stocks and carbon emissions at various geographical scales [162,163]. Producing continental [153,164] and global [165,166] carbon density maps based on site-specific empirical information is now possible ( Figure 5) in spite of the challenges involved in the development of these maps [167].…”

Section: Discussionmentioning

confidence: 99%

Trailblazing the Carbon Cycle of Tropical Forests from Puerto Rico

Brown

Lugo

2017

Forests

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Abstract:We review the literature that led to clarifying the role of tropical forests in the global carbon cycle from a time when they were considered sources of atmospheric carbon to the time when they were found to be atmospheric carbon sinks. This literature originates from work conducted by US Forest Service scientists in Puerto Rico and their collaborators. It involves the classification of forests by life zones, estimation of carbon density by forest type, assessing carbon storage changes with ecological succession and land use/land cover type, describing the details of the carbon cycle of forests at stand and landscape levels, assessing global land cover by forest type and the complexity of land use change in tropical regions, and assessing the ecological fluxes and storages that contribute to net carbon accumulation in tropical forests. We also review recent work that couples field inventory data, remote sensing technology such as LIDAR, and GIS analysis in order to more accurately determine the role of tropical forests in the global carbon cycle and point out new avenues of carbon research that address the responses of tropical forests to environmental change.

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Gap formation and carbon cycling in the Brazilian Amazon: measurement using high-resolution optical remote sensing and studies in large forest plots

Cited by 28 publications

References 57 publications

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

Airborne LiDAR Detects Selectively Logged Tropical Forest Even in an Advanced Stage of Recovery

Trailblazing the Carbon Cycle of Tropical Forests from Puerto Rico

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